---
license: apache-2.0
base_model: zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-finetuned-ausSpiders2000
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 10-finetuned-ausSpiders2000

This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co/zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0508
- Accuracy: 0.9858
- Precision: 0.9892
- Recall: 0.9865
- F1: 0.9878

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1997        | 1.0   | 281  | 0.2264          | 0.9281   | 0.9395    | 0.8869 | 0.9045 |
| 0.17          | 2.0   | 563  | 0.1382          | 0.9565   | 0.8540    | 0.8266 | 0.8381 |
| 0.21          | 3.0   | 845  | 0.1404          | 0.9583   | 0.9747    | 0.9064 | 0.9349 |
| 0.1976        | 4.0   | 1127 | 0.0987          | 0.9689   | 0.9716    | 0.8917 | 0.9128 |
| 0.178         | 5.0   | 1408 | 0.1219          | 0.9636   | 0.9393    | 0.9600 | 0.9472 |
| 0.0659        | 6.0   | 1690 | 0.0804          | 0.9813   | 0.9815    | 0.9801 | 0.9807 |
| 0.0917        | 7.0   | 1972 | 0.1062          | 0.9734   | 0.9765    | 0.9676 | 0.9716 |
| 0.108         | 8.0   | 2254 | 0.0568          | 0.9849   | 0.9868    | 0.9794 | 0.9828 |
| 0.1151        | 9.0   | 2535 | 0.0508          | 0.9858   | 0.9876    | 0.9863 | 0.9869 |
| 0.049         | 9.97  | 2810 | 0.0508          | 0.9858   | 0.9892    | 0.9865 | 0.9878 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3